Print Email Facebook Twitter An Experimental Performance Evaluation of Autoscaling Policies for Complex Workflows Title An Experimental Performance Evaluation of Autoscaling Policies for Complex Workflows Author Ilyushkin, A.S. (TU Delft Distributed Systems) Ali-Eldin, Ahmed (Umeå University) Herbst, Nikolas (University of Würzburg) Papadopoulos, Alessandro (Mälardalen University) Ghit, B.I. (TU Delft Distributed Systems) Epema, D.H.J. (TU Delft Distributed Systems) Iosup, A. (TU Delft Distributed Systems) Date 2017 Abstract Simplifying the task of resource management and scheduling for customers, while still delivering complex Quality-of-Service (QoS), is key to cloud computing. Many autoscaling policies have been proposed in the past decade to decide on behalf of cloud customers when and how to provision resources to a cloud application utilizing cloud elasticity features. However, in prior work, when a new policy is proposed, it is seldom compared to the state-of-the-art, and isoften compared only to static provisioning using a predefined QoS target. This reduces the ability of cloud customers and of cloud operators to choose and deploy an autoscaling policy. In our work, we conduct an experimental performance evaluation of autoscaling policies, using as application model workflows, a commonly used formalism for automating resource management for applications with well-defined yet complex structure. We present a detailedcomparative study of general state-of-the-art autoscaling policies, along with two new workflow-specific policies. To understand the performance differences between the 7 policies, we conduct various forms of pairwise and group comparisons. We report both individual and aggregated metrics. Our results highlight the trade-offs between the suggested policies, and thus enable a better understanding of the current state-of-the-art. To reference this document use: http://resolver.tudelft.nl/uuid:72778db7-89aa-4dc9-8105-217a2d1d6f64 DOI https://doi.org/10.1145/3030207.3030214 Publisher Association for Computing Machinery (ACM), New York, NY ISBN 978-1-4503-4404-3 Source Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering, ICPE 2017 Event ICPE 2017, 2017-04-22 → 2017-04-27, L'Aquila, Italy Part of collection Institutional Repository Document type conference paper Rights © 2017 A.S. Ilyushkin, Ahmed Ali-Eldin, Nikolas Herbst, Alessandro Papadopoulos, B.I. Ghit, D.H.J. Epema, A. Iosup Files PDF ICPE2017_ASIlyushkin.pdf 421.71 KB Close viewer /islandora/object/uuid:72778db7-89aa-4dc9-8105-217a2d1d6f64/datastream/OBJ/view